Traditionally, unsheltered Point in Time (PIT) Counts are the result of volunteers conducting an in-person head-count of individuals experiencing homelessness on a single night. This resource-intensive method is widely understood to be an undercount. It also fails to capture essential qualitative data for what people living unsheltered experience and need.

This past spring, The King County Regional Homelessness Authority (RHA) took a novel approach to the PIT. The RHA conducted the 2022 unsheltered PIT count as part of a qualitative interview process over the course of a month, using a methodology called Respondent Driven Sampling. This methodology has a strong track record for producing high-quality demographic and population estimates, confirmed by numerous studies by academic researchers and the World Health Organization.

The RHA worked with an expert statistician at the University of Washington to advise on the RDS sampling design and statistical modeling. The RHA, also, worked with the Lived Experience Coalition (LEC) volunteers to interview people living unsheltered about their lived experiences. With the RDS sampling methodology and a semi-structured qualitative interview, the RHA captured people's stories the way they wanted them to be told while providing our federal partners with estimates for the 2022 PIT Count.

During this session, we will provide an overview of how the RHA partnered with academic researchers and the LEC to execute this strategy. We will review the history of RDS for sampling vulnerable populations which lack administrative data and we cover our implementation of RDS and strategy for estimating the total unsheltered PIT count and relevant demographics. We will also discuss the qualitative component of our projects, including engaging the community in research design, partnering with LEC volunteers, designing semi-structured interviews, collecting oral histories, and lessons learned throughout this process.